Information extraction systems distill specific items of information from large quantities of text. Current literature in the field of information extraction focuses largely on how different language models and machine learning approaches can improve system accuracy, with little mention of the role of interaction between the user and the system. In this paper, we explore many opportunities for interaction and adaptation during information extraction, and propose a system design to investigate these opportunities further.

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